The Allegro Trains platform is a full system open source ML / DL experiment manager and ML-Ops solution.\nIt is composed of a Python SDK, server, Web UI, and execution agents.\nAllegro Trains enables data scientists and data engineers to effortlessly track, manage, compare, and collaborate\non their experiments as well as easily manage their training workloads on remote machines.\nAllegro Trains is designed for effortless integration so that teams can preserve their existing methods\nand practices. Use it on a daily basis to boost collaboration and visibility, or use it to automatically collect\nyour experimentation logs, outputs, and data to one centralized server.

An Auto-Magical Experiment Manager, Version Control and MLOps solution

With only two lines added to your code, the Allegro Trains Python package automatically tracks:

Git repository, branch, commit id, entry point, and local git diff
Python environment (including specific packages & versions)
stdout and stderr
Resource Monitoring (CPU/GPU utilization, temperature, IO, network, etc.)
Hyper-parameters\n
- ArgParser for command line parameters with currently used values
- Explicit parameters dictionary
- TensorFlow Defines (absl-py)
\n
Initial model weights file
Model snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http)
Artifacts log & store (Shared folder, S3, GS, Azure, Http)
Tensorboard/TensorboardX scalars, metrics, histograms, images (with audio coming soon)
Matplotlib & Seaborn

> Supported frameworks: Tensorflow, PyTorch, Keras, XGBoost and Scikit-Learn (MxNet is coming soon)\n> Includes seamless integration (including version control) with Jupyter Notebook\nand PyCharm remote debugging

Use the Trains Demo Server to try out Trains and test your code with no additional setup.

For more information on using the Trains python package, see our Quick Start Guide or the complete Trains Documentation page.

Trains Agent: Simple and Flexible Experiment Orchestration

Using the Trains Agent and zero configuration, you can now set up a dynamic AI experiment cluster

Trains Agent was built to address the DL/ML R&D DevOps needs:

Easily add & remove machines from the cluster
Reuse machines without the need for any dedicated containers or images
Combine GPU resources across any cloud and on-prem
No need for yaml/json/template configuration of any kind
User-friendly UI
Manageable resource allocation that can be used by researchers and engineers
Flexible and controllable scheduler with priority support
Automatic instance spinning in the cloud (coming soon)

Trains Agent executes experiments using the following process

Create a new virtual environment (or launch the selected docker image)
Clone the code into the virtual-environment (or inside the docker)
Install python packages based on the package requirements listed for the experiment\n
- Special note for PyTorch: The Trains Agent will automatically select the\ntorch packages based on the CUDA_VERSION environment variable of the machine
\n
Execute the code while monitoring the process
Log all stdout/stderr in the Trains UI, including the cloning and installation process, for easy debugging
Monitor the execution and allow you to manually abort the job using the Trains UI (or, in the unfortunate case of a code crash, catch the error and signal the experiment has failed)

For more information on using the Trains Agent, see Using the Trains Agent or the complete Trains Documentation page.

Deploying the Allegro Trains platform

The Trains Server is the backend service infrastructure for Trains.\nIt allows multiple users to collaborate and manage their experiments.\nBy default, Allegro Trains is set up to work with the Trains Demo Server, which is open to anyone and resets periodically.\nIn order to host your own server, you will need to install Trains Server and point Trains to it.

Trains Server contains the following components:

The Trains Web-App, a single-page UI for experiment management and browsing
RESTful API for:\n
- Documenting and logging experiment information, statistics, and results
- Querying experiments history, logs, and results
\n
Locally-hosted file server for storing images and models making them easily accessible using the Trains Web-App

Follow the instructions below to add and deploy Trains Server (and Trains Agents) to your Kubernetes clusters using Helm.

Prerequisites

\n
a Kubernetes cluster
\n
\n
kubectl is installed and configured (see Install and Set Up kubectl in the Kubernetes documentation)
\n
\n
helm installed (see Installing Helm in the Helm documentation)
\n
\n
one node labeled app: trains
\n
Important: Trains Server deployment uses node storage. If more than one node is labeled as app: trains and you redeploy or update later, then Trains Server may not locate all of your data.
\n

Set the required Elasticsearch configuration for Docker

Trains Server uses Elasticsearch which requires some specific system settings (for more information, see Notes for production use and defaults):

\n
Connect to the node you labeled as app=trains
\n
If your system contains a /etc/sysconfig/docker Docker configuration file, Add the options in quotes to the available arguments in the OPTIONS section:\nOPTIONS=\"--default-ulimit nofile=1024:65536 --default-ulimit memlock=-1:-1\"
\n
Otherwise, edit /etc/docker/daemon.json (if it exists) or create it (if it does not exist).
\nAdd or modify the defaults-ulimits section as shown below. Be sure the defaults-ulimits section contains the nofile and memlock sub-sections and values shown.
\n
Note: Your configuration file may contain other sections. If so, confirm that the sections are separated by commas (valid JSON format). For more information about Docker configuration files, see Daemon configuration file, in the Docker documentation.
\n
The Trains Server required defaults values are (json):
\n
```
 {\n     \"default-ulimits\": {\n         \"nofile\": {\n             \"name\": \"nofile\",\n             \"hard\": 65536,\n             \"soft\": 1024\n         },\n         \"memlock\":\n         {\n             \"name\": \"memlock\",\n             \"soft\": -1,\n             \"hard\": -1\n         }\n     }\n }\n
```
\n
\n
Set the Maximum Number of Memory Map Areas
\n
Elastic requires that the vm.max_map_count kernel setting, which is the maximum number of memory map areas a process can use, is set to at least 262144.
\n
For CentOS 7, Ubuntu 16.04, Mint 18.3, Ubuntu 18.04 and Mint 19.x, we tested the following commands to set vm.max_map_count:
\n
```
 echo \"vm.max_map_count=262144\" &gt; /tmp/99-trains.conf\n sudo mv /tmp/99-trains.conf /etc/sysctl.d/99-trains.conf\n sudo sysctl -w vm.max_map_count=262144\n
```
\n
For information about setting this parameter on other systems, see the elastic documentation.
\n
\n
Restart docker:
\n
```
 sudo service docker restart\n
```
\n

Add Trains Server and Agents to the Kubernetes Cluster Using Helm

Fetch the Trains Helm chart to your local directory:

 helm fetch https://helm.ngc.nvidia.com/partners/charts/trains-chart-0.14.1+1.tgz\n

\n
By default, the Trains Server deployment uses storage on a single node (labeled app=trains).\nTo change the type of storage used (for example NFS), see Configuring trains-server storage for NFS.
\n
\n
By default, one instance of Trains Agent is created in the trains Kubernetes cluster.\nTo change this setting, create a local values.yaml as specified in Configuring Trains Agents in your cluster.
\n
\n
Install trains-chart on your cluster:
\n
```
 helm install trains-chart-0.14.1+1.tgz --namespace=trains --name trains-server\n
```
\n
Alternatively, in case you've created a local values.yaml file, use:
\n
```
 helm install trains-chart-0.14.1+1.tgz --namespace=trains --name trains-server --values values.yaml\n
```
\n
A trains namespace is created in your cluster and Trains Server and Agent(s) are deployed in it.
\n

Network Configuration

Accessing the Trains Server

After the Trains Server is deployed, the services expose the following node ports:

API server on 30008
Web server on 30080
File server on 30081

For example, to access the Trains Web-App point your browser to http://[trains-server-node-ip]:30080 where the Trains Server node is the node labeled app=trains.

Accessing the Trains Server using subdomains

Access Trains Server by creating a load balancer and domain name with records pointing to the load balancer.

Once you have a load balancer and domain name set up, follow these steps to configure access Trains Server on your Kubernetes cluster:

\n
Create domain records
\n
- \n
  Create 3 records to be used for Trains Web-App, File server and API access using the following rules:
  \n
  - app.[your domain name]
  - files.[your domain name]
  - api.[your domain name]
  \n
  For example, app.trains.mydomainname.com, files.trains.mydomainname.com and api.trains.mydomainname.com
  \n
\n
\n
Point the records you created to the load balancer
\n
\n
Configure the load balancer to redirect traffic coming from the records you created:
\n
- app.[your domain name] should be redirected to Kubernetes Trains Server node on port 30080
- files.[your domain name] should be redirected to Kubernetes Trains Server node on port 30081
- api.[your domain name] should be redirected to Kubernetes Trains Server node on port 30008
\n

Configuring Trains Agents in your cluster

In order to create Trains Agent instances as part of your deployment, create or update your local values.yaml file.\nThis values.yaml file should be used in your helm install command (see Deploying trains-server in Kubernetes Clusters Using Helm)

The file must contain the following values in the agent section:

numberOfTrainsAgents: controls the number of Trains Agent pods to be deployed. Each Agent pod will listen for and execute experiments from the Trains Server
nvidiaGpusPerAgent: defines the number of GPUs required by each Agent pod
trainsApiHost: the URL used to access the Trains API server, as defined in your load-balancer (usually https://api.[your domain name], see Accessing trains-server)
trainsWebHost: the URL used to access the Trains Web-App, as defined in your load-balancer (usually https://app.[your domain name], see Accessing trains-server)
trainsFilesHost: the URL used to access the Trains File Server, as defined in your load-balancer (usually https://files.[your domain name], see Accessing trains-server)

Additional optional values in the agent section include:

defaultBaseDocker: the default docker image used by the Agent running in the Agent pod in order to execute an experiment. Default is nvidia/cuda.
agentVersion: determines the specific Agent version to be used in the deployment, for example \"==0.13.3\". Default is null (use latest version)
trainsGitUser / trainsGitPassword: GIT credentials used by Trains Agent running an experiment when cloning the GIT repository defined in the experiment, if defined. Default is null (not used)
awsAccessKeyId / awsSecretAccessKey / awsDefaultRegion: AWS account info used by the Trains Python package when uploading files to an AWS S3 buckets (not required if only using the default Trains File Server). Default is null (not used)
azureStorageAccount / azureStorageKey: Azure account info used by the Trains Python package when uploading files to MS Azure Blob Service (not required if only using the default Trains File Server). Default is null (not used)

For example, the following values.yaml file requests 4 Agent instances in your deployment (see chart-example-values.yaml):

agent:\n  numberOfTrainsAgents: 4\n  nvidiaGpusPerAgent: 1\n  defaultBaseDocker: \"nvidia/cuda\"\n  trainsApiHost: \"https://api.trains.mydomain.com\"\n  trainsWebHost: \"https://app.trains.mydomain.com\"\n  trainsFilesHost: \"https://files.trains.mydomain.com\"\n  trainsGitUser: null\n  trainsGitPassword: null\n  awsAccessKeyId: null\n  awsSecretAccessKey: null\n  awsDefaultRegion: null\n  azureStorageAccount: null\n  azureStorageKey: null\n

Configuring trains-server storage for NFS

The Trains Server deployment uses a PersistentVolume of type HostPath,\nwhich uses a fixed path on the node labeled app: trains.

The existing chart supports changing the volume type to NFS,\nby setting the use_nfs value and configuring the NFS persistent volume using additional values in your local values.yaml file:

storage:\n  use_nfs: true\n  nfs:\n    server: \"[nfs-server-ip-address]\"\n    base_path: \"/nfs/path/for/trains/data\"\n

Additional Configuration for trains-server

You can also configure the Trains Server for:

fixed users (users with credentials)
non-responsive experiment watchdog settings

For detailed instructions, see Configuring Trains Server in the Trains Documentation page.

License Information

Trains Python Package is provided under the Apache License, Version 2.0
Trains Agent is provided under the Apache License, Version 2.0
Trains Server is provided under the Server Side Public License v1.0

Documentation, Community & Support

Allegro Trains documentation is available here

For more examples and use cases, check examples.

If you have any questions: post on our Slack Channel, or tag your questions on stackoverflow with 'trains' tag.

For feature requests or bug reports, please use GitHub issues.

Additionally, you can always find us at trains@allegro.ai

","resourceVersions",[192,193],"resourceVersionsTotal","hasMoreVersions","versionMetadata",{"_175":28,"_176":-5,"_52":81,"_78":-5,"_82":177,"_84":178,"_179":80,"_90":91,"_87":34,"_180":-5,"_86":34,"_181":-5,"_182":34,"_183":-5,"_184":34,"_185":-5,"_186":34,"_187":-5,"_188":34,"_189":-5,"_190":34,"_88":191},"versionNotFound","isLoggedIn","latestVersionPath","/orgs/partners/allegro/helm-charts/trains-chart/-","version","-","imageReference","cliDownloadCommand","helmFetchCommand","helm pull https://helm.ngc.nvidia.com/partners/allegro/charts/trains-chart-0.14.1+1.tgz","viewAllVersionsPath","/orgs/partners/allegro/helm-charts/trains-chart/-/version-history","accessCheckResult",{"_174":94},"hasRelatedCollections","context",{"_170":171,"_172":173},1789403548768,[],[],[163,164,165,166,167,168,169],{"_48":63,"_50":73,"_52":65,"_54":66,"_56":74,"_58":59},{"_48":63,"_50":71,"_52":65,"_54":66,"_56":72,"_58":59},{"_48":63,"_50":70,"_52":110,"_54":-5,"_56":-5,"_58":59},{"_48":63,"_50":68,"_52":65,"_54":66,"_56":69,"_58":59},{"_48":63,"_50":64,"_52":65,"_54":66,"_56":67,"_58":59},{"_48":60,"_50":61,"_52":53,"_54":55,"_56":62,"_58":59},{"_48":49,"_50":51,"_52":53,"_54":55,"_56":57,"_58":59},"orgName","partners","teamName","allegro","allowed","versionId","description",["D",1589412046025],["D",1589412046025],"totalSizeInBytes","malwareScanStatus","releaseNotes","hasReleaseNotes","setup","hasSetup","quickStartGuide","hasQuickStartGuide","advanced","hasAdvanced","performance","hasPerformance",[],{"_76":147,"_77":195,"_78":-5,"_87":34,"_86":34,"_88":194,"_182":34},{"_76":28,"_77":28,"_78":-5,"_87":34,"_86":34,"_88":194,"_182":34},[],"Latest (0.14.1+1)","partners/allegro/trains-chart","key","partners/allegro/helm-charts/trains-chart","resourceId","trains-chart","shortDescription","Allegro Trains delivers an optimized, seamless, and scalable solution for training on DGX machines with ML-Ops and experiment management features.","The Allegro Trains platform is a full system open source ML / DL experiment manager and ML-Ops solution.\nIt is composed of a Python SDK, server, Web UI, and execution agents.\nAllegro Trains enables data scientists and data engineers to effortlessly track, manage, compare, and collaborate\non their experiments as well as easily manage their training workloads on remote machines.\nAllegro Trains is designed for effortless integration so that teams can preserve their existing methods\nand practices. Use it on a daily basis to boost collaboration and visibility, or use it to automatically collect\nyour experimentation logs, outputs, and data to one centralized server.\n\n### An Auto-Magical Experiment Manager, Version Control and MLOps solution\n\n**With only two lines added to your code, the [Allegro Trains](https://github.com/allegroai/trains) Python package automatically tracks:**\n\n* Git repository, branch, commit id, entry point, and local git diff\n* Python environment (including specific packages & versions)\n* stdout and stderr\n* Resource Monitoring (CPU/GPU utilization, temperature, IO, network, etc.)\n* Hyper-parameters\n * ArgParser for command line parameters with currently used values\n * Explicit parameters dictionary\n * TensorFlow Defines (absl-py)\n* Initial model weights file\n* Model snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http)\n* Artifacts log & store (Shared folder, S3, GS, Azure, Http)\n* Tensorboard/TensorboardX scalars, metrics, histograms, images (with audio coming soon)\n* Matplotlib & Seaborn\n\n> Supported frameworks: Tensorflow, PyTorch, Keras, XGBoost and Scikit-Learn (MxNet is coming soon)\n> Includes seamless integration (including version control) with [*Jupyter Notebook*](https://github.com/allegroai/trains-jupyter-plugin)\n and [*PyCharm* remote debugging](https://github.com/allegroai/trains-pycharm-plugin)\n\n**Use the [Trains Demo Server](https://demoapp.trains.allegro.ai) to try out Trains and [test your code](https://github.com/allegroai/trains#using-trains-) with no additional setup.**\n\n

\n\n**For more information on using the Trains python package, see our [Quick Start Guide](https://github.com/allegroai/trains#using-trains-) or the complete [Trains Documentation](https://allegro.ai/docs/) page.**\n\n### Trains Agent: Simple and Flexible Experiment Orchestration\n\n**Using the [Trains Agent](https://github.com/allegroai/trains-agent) and zero configuration, you can now set up a dynamic AI experiment cluster**\n\n**Trains Agent was built to address the DL/ML R&D DevOps needs:**\n\n* Easily add & remove machines from the cluster\n* Reuse machines without the need for any dedicated containers or images\n* **Combine GPU resources across any cloud and on-prem**\n* **No need for yaml/json/template configuration of any kind**\n* **User-friendly UI**\n* Manageable resource allocation that can be used by researchers and engineers\n* Flexible and controllable scheduler with priority support\n* Automatic instance spinning in the cloud **(coming soon)**\n\n**Trains Agent executes experiments using the following process**\n - Create a new virtual environment (or launch the selected docker image)\n - Clone the code into the virtual-environment (or inside the docker)\n - Install python packages based on the package requirements listed for the experiment\n - Special note for PyTorch: The Trains Agent will automatically select the\n torch packages based on the CUDA_VERSION environment variable of the machine\n - Execute the code while monitoring the process\n - Log all stdout/stderr in the Trains UI, including the cloning and installation process, for easy debugging\n - Monitor the execution and allow you to manually abort the job using the Trains UI (or, in the unfortunate case of a code crash, catch the error and signal the experiment has failed)\n\n**For more information on using the Trains Agent, see [Using the Trains Agent](https://github.com/allegroai/trains-agent/#using-the-trains-agent) or the complete [Trains Documentation](https://allegro.ai/docs/) page.**\n\n## Deploying the Allegro Trains platform\n \nThe [Trains Server](https://github.com/allegroai/trains-server) is the backend service infrastructure for [Trains](https://github.com/allegroai/trains).\nIt allows multiple users to collaborate and manage their experiments.\nBy default, Allegro Trains is set up to work with the Trains Demo Server, which is open to anyone and resets periodically.\nIn order to host your own server, you will need to install Trains Server and point Trains to it.\n\nTrains Server contains the following components:\n* The Trains Web-App, a single-page UI for experiment management and browsing\n* RESTful API for:\n * Documenting and logging experiment information, statistics, and results\n * Querying experiments history, logs, and results\n* Locally-hosted file server for storing images and models making them easily accessible using the Trains Web-App\n\nFollow the instructions below to add and deploy Trains Server (and Trains Agents) to your Kubernetes clusters using Helm.\n\n### Prerequisites\n\n* a Kubernetes cluster\n* `kubectl` is installed and configured (see [Install and Set Up kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/) in the Kubernetes documentation)\n* `helm` installed (see [Installing Helm](https://helm.sh/docs/using_helm/#installing-helm) in the Helm documentation)\n* one node labeled `app: trains`\n\n **Important**: Trains Server deployment uses node storage. If more than one node is labeled as `app: trains` and you redeploy or update later, then Trains Server may not locate all of your data.\n\n### Set the required Elasticsearch configuration for Docker\nTrains Server uses Elasticsearch which requires some specific system settings (for more information, see [Notes for production use and defaults](https://www.elastic.co/guide/en/elasticsearch/reference/master/docker.html#_notes_for_production_use_and_defaults)):\n1. Connect to the node you labeled as `app=trains` \n\n If your system contains a `/etc/sysconfig/docker` Docker configuration file, Add the options in quotes to the available arguments in the `OPTIONS` section:\n `OPTIONS=\"--default-ulimit nofile=1024:65536 --default-ulimit memlock=-1:-1\"`\n \n Otherwise, edit `/etc/docker/daemon.json` (if it exists) or create it (if it does not exist). \n Add or modify the `defaults-ulimits` section as shown below. Be sure the `defaults-ulimits` section contains the `nofile` and `memlock` sub-sections and values shown.\n \n **Note**: Your configuration file may contain other sections. If so, confirm that the sections are separated by commas (valid JSON format). For more information about Docker configuration files, see [Daemon configuration file](https://docs.docker.com/engine/reference/commandline/dockerd/#daemon-configuration-file), in the Docker documentation. \n \n The Trains Server required defaults values are (json):\n ```\n {\n \"default-ulimits\": {\n \"nofile\": {\n \"name\": \"nofile\",\n \"hard\": 65536,\n \"soft\": 1024\n },\n \"memlock\":\n {\n \"name\": \"memlock\",\n \"soft\": -1,\n \"hard\": -1\n }\n }\n }\n ```\n \n1. Set the Maximum Number of Memory Map Areas \n \n Elastic requires that the vm.max_map_count kernel setting, which is the maximum number of memory map areas a process can use, is set to at least 262144. \n\n For CentOS 7, Ubuntu 16.04, Mint 18.3, Ubuntu 18.04 and Mint 19.x, we tested the following commands to set vm.max_map_count: \n ```\n echo \"vm.max_map_count=262144\" > /tmp/99-trains.conf\n sudo mv /tmp/99-trains.conf /etc/sysctl.d/99-trains.conf\n sudo sysctl -w vm.max_map_count=262144\n ```\n For information about setting this parameter on other systems, see the [elastic documentation](https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#docker-cli-run-prod-mode).\n\n1. Restart docker:\n ```\n sudo service docker restart\n ```\n \n### Add Trains Server and Agents to the Kubernetes Cluster Using Helm\n\n1. Fetch the Trains Helm chart to your local directory:\n\n helm fetch https://helm.ngc.nvidia.com/partners/charts/trains-chart-0.14.1+1.tgz\n\n1. By default, the Trains Server deployment uses storage on a single node (labeled `app=trains`).\nTo change the type of storage used (for example NFS), see [Configuring trains-server storage for NFS](#configure-trains-server-storage-nfs).\n\n1. By default, one instance of Trains Agent is created in the `trains` Kubernetes cluster.\nTo change this setting, create a local `values.yaml` as specified in [Configuring Trains Agents in your cluster](#configure-trains-agents).\n\n1. Install `trains-chart` on your cluster:\n\n helm install trains-chart-0.14.1+1.tgz --namespace=trains --name trains-server\n\n Alternatively, in case you've created a local `values.yaml` file, use:\n\n helm install trains-chart-0.14.1+1.tgz --namespace=trains --name trains-server --values values.yaml\n\n A `trains` namespace is created in your cluster and Trains Server and Agent(s) are deployed in it.\n\n\n## Network Configuration\n\n### Accessing the Trains Server\n\nAfter the Trains Server is deployed, the services expose the following node ports:\n\n* API server on `30008`\n* Web server on `30080`\n* File server on `30081`\n\nFor example, to access the Trains Web-App point your browser to `http://[trains-server-node-ip]:30080` where the Trains Server node is the node labeled `app=trains`. \n\n### Accessing the Trains Server using subdomains\n\nAccess Trains Server by creating a load balancer and domain name with records pointing to the load balancer.\n\nOnce you have a load balancer and domain name set up, follow these steps to configure access Trains Server on your Kubernetes cluster:\n\n1. Create domain records\n\n * Create 3 records to be used for Trains Web-App, File server and API access using the following rules:\n * `app.[your domain name]`\n * `files.[your domain name]`\n * `api.[your domain name]`\n\n For example, `app.trains.mydomainname.com`, `files.trains.mydomainname.com` and `api.trains.mydomainname.com`\n2. Point the records you created to the load balancer\n3. Configure the load balancer to redirect traffic coming from the records you created:\n * `app.[your domain name]` should be redirected to Kubernetes Trains Server node on port `30080`\n * `files.[your domain name]` should be redirected to Kubernetes Trains Server node on port `30081`\n * `api.[your domain name]` should be redirected to Kubernetes Trains Server node on port `30008`\n\n## Configuring Trains Agents in your cluster\n\nIn order to create Trains Agent instances as part of your deployment, create or update your local `values.yaml` file.\nThis `values.yaml` file should be used in your `helm install` command (see [Deploying trains-server in Kubernetes Clusters Using Helm](#deploying-trains-server))\n\nThe file must contain the following values in the `agent` section:\n\n- `numberOfTrainsAgents`: controls the number of Trains Agent pods to be deployed. Each Agent pod will listen for and execute experiments from the Trains Server\n- `nvidiaGpusPerAgent`: defines the number of GPUs required by each Agent pod\n- `trainsApiHost`: the URL used to access the Trains API server, as defined in your load-balancer (usually `https://api.[your domain name]`, see [Accessing trains-server](#accessing-trains-server))\n- `trainsWebHost`: the URL used to access the Trains Web-App, as defined in your load-balancer (usually `https://app.[your domain name]`, see [Accessing trains-server](#accessing-trains-server))\n- `trainsFilesHost`: the URL used to access the Trains File Server, as defined in your load-balancer (usually `https://files.[your domain name]`, see [Accessing trains-server](#accessing-trains-server))\n\nAdditional optional values in the `agent` section include:\n\n- `defaultBaseDocker`: the default docker image used by the Agent running in the Agent pod in order to execute an experiment. Default is `nvidia/cuda`.\n- `agentVersion`: determines the specific Agent version to be used in the deployment, for example `\"==0.13.3\"`. Default is `null` (use latest version)\n- `trainsGitUser` / `trainsGitPassword`: GIT credentials used by Trains Agent running an experiment when cloning the GIT repository defined in the experiment, if defined. Default is `null` (not used)\n- `awsAccessKeyId` / `awsSecretAccessKey` / `awsDefaultRegion`: AWS account info used by the Trains Python package when uploading files to an AWS S3 buckets (not required if only using the default Trains File Server). Default is `null` (not used)\n- `azureStorageAccount` / `azureStorageKey`: Azure account info used by the Trains Python package when uploading files to MS Azure Blob Service (not required if only using the default Trains File Server). Default is `null` (not used)\n\nFor example, the following `values.yaml` file requests 4 Agent instances in your deployment (see [chart-example-values.yaml](https://github.com/allegroai/trains-server-k8s/blob/master/docs/chart-example-values.yaml)):\n```yaml\nagent:\n numberOfTrainsAgents: 4\n nvidiaGpusPerAgent: 1\n defaultBaseDocker: \"nvidia/cuda\"\n trainsApiHost: \"https://api.trains.mydomain.com\"\n trainsWebHost: \"https://app.trains.mydomain.com\"\n trainsFilesHost: \"https://files.trains.mydomain.com\"\n trainsGitUser: null\n trainsGitPassword: null\n awsAccessKeyId: null\n awsSecretAccessKey: null\n awsDefaultRegion: null\n azureStorageAccount: null\n azureStorageKey: null\n```\n\n## Configuring trains-server storage for NFS\n\nThe Trains Server deployment uses a `PersistentVolume` of type `HostPath`,\nwhich uses a fixed path on the node labeled `app: trains`.\n\nThe existing chart supports changing the volume type to `NFS`,\nby setting the `use_nfs` value and configuring the NFS persistent volume using additional values in your local `values.yaml` file:\n```yaml\nstorage:\n use_nfs: true\n nfs:\n server: \"[nfs-server-ip-address]\"\n base_path: \"/nfs/path/for/trains/data\"\n```\n\n## Additional Configuration for trains-server\n\nYou can also configure the Trains Server for:\n\n* fixed users (users with credentials)\n* non-responsive experiment watchdog settings\n\nFor detailed instructions, see [Configuring Trains Server](https://allegro.ai/docs/deploying_trains/trains_server_config/) in the [Trains Documentation](https://allegro.ai/docs/) page.\n\n## License Information\n\n- [Trains](https://github.com/allegroai/trains) Python Package is provided under the [Apache License, Version 2.0](https://github.com/allegroai/trains#license)\n- [Trains Agent](https://github.com/allegroai/trains-agent) is provided under the [Apache License, Version 2.0](https://github.com/allegroai/trains-agent)\n- [Trains Server](https://github.com/allegroai/trains-server) is provided under the [Server Side Public License v1.0](https://github.com/allegroai/trains-server#license)\n\n## Documentation, Community & Support\n\nAllegro Trains documentation is available [here](https://allegro.ai/docs)\n\nFor more examples and use cases, check [examples](https://github.com/allegroai/trains/blob/master/docs/trains_examples.md).\n\nIf you have any questions: post on our [Slack Channel](https://join.slack.com/t/allegroai-trains/shared_invite/enQtOTQyMTI1MzQxMzE4LTY5NTUxOTY1NmQ1MzQ5MjRhMGRhZmM4ODE5NTNjMTg2NTBlZGQzZGVkMWU3ZDg1MGE1MjQxNDEzMWU2NmVjZmY), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/trains) with '**trains**' tag.\n\nFor feature requests or bug reports, please use [GitHub issues](https://github.com/allegroai/trains/issues).\n\nAdditionally, you can always find us at *trains@allegro.ai*","displayName","Allegro Trains Server",["D",1680648048847],"publisher","Allegro AI","latestVersion","collectionCounts","imageUrl","/api/image/partners/allegro/helm-charts/trains-chart","rawImageUrl","https://assets.nvidiagrid.net/ngc/logos/ISV-OSS-Non-Nvidia-Publishing-allegro.png","canGuestDownload","latestVersionSizeInBytes","licenseTerms","isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[],"displayLabels",[235,236,237,238,239,240,241],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_204":266,"_243":266,"_245":267,"_247":248},{"_204":263,"_243":264,"_245":265,"_247":248},{"_204":260,"_243":261,"_245":262,"_247":248},{"_204":257,"_243":258,"_245":259,"_247":248},{"_204":253,"_243":254,"_245":255,"_247":248},{"_204":251,"_243":251,"_245":252,"_247":248},{"_204":242,"_243":244,"_245":246,"_247":248},"Retail","value","indus_retail","filter",{"_249":250,"_243":244},"category","label","field","industry","Multi-Node",{"_249":248,"_243":251},"ML","soln_ml",{"_249":256,"_243":254},"technology","Manufacturing","indus_manufacturing",{"_249":250,"_243":258},"Infrastructure Software","soln_infrastructure_software",{"_249":256,"_243":261},"DL","soln_dl",{"_249":256,"_243":264},"DGX-ready Software",{"_249":248,"_243":266},{"_115":1249,"_117":1250},"ngcApps",[1202],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1183":1184,"_1185":1186,"_1187":1188,"_1189":1190,"_1191":279,"_146":305,"_1192":1193,"_1194":59,"_1195":94,"_1196":94,"_1197":1198,"_1199":94,"_1200":1201},"amplitude",{"_1180":1181,"_816":-7,"_1182":34},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1174":1175,"_1176":1177,"_1178":1179},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1789403548622,"1.15.0","defaultSearchSuggestions",{"_1056":384,"_1057":1058,"_1059":1060,"_1061":1062},"announcements",[],"consentState",{"_341":1046,"_1047":94,"_1048":34,"_1049":34,"_1050":1051},"consentConfig",{"_323":324,"_325":326,"_327":328,"_329":330,"_331":332,"_333":334,"_335":336,"_337":338,"_339":340,"_341":342},"showContactAdmin",[],[],[318,319,320,321,322],{"_48":63,"_50":73,"_52":110,"_54":-5,"_56":-5,"_58":59},{"_48":63,"_50":71,"_52":110,"_54":-5,"_56":-5,"_58":59},{"_48":63,"_50":68,"_52":110,"_54":-5,"_56":-5,"_58":59},{"_48":60,"_50":61,"_52":110,"_54":-5,"_56":-5,"_58":59},{"_48":49,"_50":51,"_52":110,"_54":-5,"_56":-5,"_58":59},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. The information collected might relate to you, your preferences, or your device. We use that information to make the site work, analyze performance and traffic on our website, provide a more personalized web experience, and assist in our marketing efforts.

Under certain privacy laws, you have the right to direct us not to \"sell\" or \"share\" your personal information for targeted advertising. To opt-out of the \"sale\" and \"sharing\" of personal information through cookies, you must opt-out of optional cookies using the toggles below. To opt out of the \"sale\" and \"sharing\" of data collected by other means (e.g., online forms) you must also update your data sharing preferences through the NVIDIA Preference Center.

Click on the different category headings below to find out more and change the settings according to your preference. You cannot opt out of Required Cookies as they are deployed to ensure the proper functioning of our website (such as prompting the cookie banner and remembering your settings, etc.). By clicking \"Save and Accept\" or \"Decline All\" at the bottom, you consent to the use of cookies and other tools as described in our Cookie Policy in accordance with your settings and accept our Terms of Service (which contains important waivers). For more information about our privacy practices, please see our Privacy Policy.","mainText","Cookie Settings","alertNoticeText",{"_1038":1039,"_1040":1041,"_1042":1043,"_1044":1045},"bannerAcceptLabel","Accept All","bannerRejectLabel","Reject Optional","bannerSettingsLabel","Manage Settings","preferenceSaveLabel","Save Choices","preferenceRejectLabel","Decline All","alwaysActiveText","Always Active","groups",[343,344,345,346,347],{"_348":728,"_77":729,"_176":730,"_352":94,"_353":16,"_355":731,"_357":732},{"_348":631,"_77":632,"_176":633,"_352":34,"_353":57,"_355":634,"_357":635},{"_348":539,"_77":540,"_176":541,"_352":34,"_353":62,"_355":542,"_357":543},{"_348":359,"_77":360,"_176":361,"_352":34,"_353":362,"_355":363,"_357":364},{"_348":349,"_77":350,"_176":351,"_352":34,"_353":354,"_355":356,"_357":358},"optanonGroupId","C0005","Social Media Cookies","These cookies are set by a range of social media services that we have added to the site to enable you to share our content with your friends and networks. They are capable of tracking your browser across other sites and building up a profile of your interests. This may impact the content and messages you see on other websites you visit. If you do not allow these cookies you may not be able to use or see these sharing tools.","alwaysActive","order",11,"cookies",[],"hosts",[],"C0004","Advertising Cookies","These cookies record your visit to our websites, the pages you have visited and the links you have followed to influence the advertisements that you see on other websites. These cookies and the information they collect may be managed by other companies, including our advertising partners, and may be used to build a profile of your interests and show you relevant advertising on other sites. We and our advertising partners will use this information to make our websites and the advertising displayed on it, more relevant to your interests.",5,[481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502],[365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381],{"_382":476,"_204":476,"_176":384,"_355":477},{"_382":472,"_204":472,"_176":384,"_355":473},{"_382":467,"_204":467,"_176":384,"_355":468},{"_382":463,"_204":463,"_176":384,"_355":464},{"_382":458,"_204":458,"_176":384,"_355":459},{"_382":453,"_204":453,"_176":384,"_355":454},{"_382":445,"_204":445,"_176":384,"_355":446},{"_382":437,"_204":437,"_176":384,"_355":438},{"_382":432,"_204":432,"_176":384,"_355":433},{"_382":427,"_204":427,"_176":384,"_355":428},{"_382":422,"_204":422,"_176":384,"_355":423},{"_382":417,"_204":417,"_176":384,"_355":418},{"_382":412,"_204":412,"_176":384,"_355":413},{"_382":405,"_204":405,"_176":384,"_355":406},{"_382":400,"_204":400,"_176":384,"_355":401},{"_382":393,"_204":393,"_176":384,"_355":394},{"_382":383,"_204":383,"_176":384,"_355":385},"hostName","amazon-adsystem.com","",[386,387],{"_77":392,"_389":383,"_390":34,"_176":391},{"_77":388,"_389":383,"_390":34,"_176":391},"ad-privacy","host","isSession","This domain is owned by online retailer Amazon and is used as part of its affiliate marketing programme.","ad-id","doubleclick.net",[395,396],{"_77":399,"_389":393,"_390":34,"_176":398},{"_77":397,"_389":393,"_390":34,"_176":398},"IDE","This domain is owned by Doubleclick (Google). The main business activity is: Doubleclick is Googles real time bidding advertising exchange","test_cookie","bing.com",[402],{"_77":403,"_389":400,"_390":34,"_176":404},"MUID","This domain is owned by Mircosoft - it is the site for the search engine Bing.","assets.adobedtm.com",[407,408],{"_77":411,"_389":405,"_390":34,"_176":410},{"_77":409,"_389":405,"_390":34,"_176":410},"kndctr_F207D74D549850760A4C98C6_AdobeOrg_*","If you know anything about this host and its uses please add your contributions here. ","kndctr_F207D74D549850760A4C98C6_AdobeOrg_consent","tiktok.com",[414],{"_77":415,"_389":412,"_390":34,"_176":416},"_ttp","TikTok is a social media platform owned by ByteDance, known for short-form video sharing. The service is used to create and share videos, and it utilizes cookies for various purposes including advertising and analytics.","t.co",[419],{"_77":420,"_389":417,"_390":34,"_176":421},"muc_ads","This domain is owned by Twitter. It is used as a URL shortening service, which allows Twitter to collect data on how links are shared.","snowplow.com",[424],{"_77":425,"_389":422,"_390":34,"_176":426},"sp","Testing","google.com",[429],{"_77":430,"_389":427,"_390":34,"_176":431},"NID","This domain is owned by Google Inc. Although Google is primarily known as a search engine, the company provides a diverse range of products and services. Its main source of revenue however is advertising. Google tracks users extensively both through its own products and sites, and the numerous technologies embedded into many millions of websites around the world. It uses the data gathered from most of these services to profile the interests of web users and sell advertising space to organisations based on such interest profiles as well as aligning adverts to the content on the pages where its customer's adverts appear.","linkedin.com",[434],{"_77":435,"_389":432,"_390":34,"_176":436},"bcookie","This domain is owned by LinkedIn, the business networking platform. It typically acts as a third party host where website owners have placed one of its content sharing buttons in their pages, although its content and services can be embedded in other ways. Although such buttons add functionality to the website they are on, cookies are set regardless of whether or not the visitor has an active Linkedin profile, or agreed to their terms and conditions. For this reason it is classified as a primarily tracking/targeting domain.","twitter.com",[439,440],{"_77":443,"_389":437,"_390":34,"_176":444},{"_77":441,"_389":437,"_390":34,"_176":442},"personalization_id","This domain is owned by Twitter. The main business activity is: Social Networking Services. Where twitter acts as a third party host, it collects data through a range of plug-ins and integrations, that is primarily used for tracking and targeting.","guest_*","This domain is owned by X (formerly Twitter). The main business activity is: Social Networking Services. Where X (formerly Twitter) acts as a third party host, it collects data through a range of plug-ins and integrations, that is primarily used for tracking and targeting.","youtube.com",[447,448],{"_77":451,"_389":445,"_390":34,"_176":452},{"_77":449,"_389":445,"_390":34,"_176":450},"VISITOR_INFO1_LIVE","This cookie is used as a unique identifier to track viewing of videos","__Secure-*","YouTube is a Google owned platform for hosting and sharing videos. YouTube collects user data through videos embedded in websites, which is aggregated with profile data from other Google services in order to display targeted advertising to web visitors across a broad range of their own and other websites.","demdex.net",[455],{"_77":456,"_389":453,"_390":34,"_176":457},"demdex","This cookie helps Adobe Audience Manger perform basic functions such as visitor identification, ID synchronization, segmentation, modeling, reporting, etc.","im-apps.net",[460],{"_77":461,"_389":458,"_390":34,"_176":462},"receive-cookie-deprecation","This domain is owned by im-apps.net which provides information and resources about various instant messaging (IM) applications to help users make informed decisions based on their communication needs.","influ2.com",[465],{"_77":466,"_389":463,"_390":34,"_176":426},"R","6sc.co",[469],{"_77":470,"_389":467,"_390":34,"_176":471},"6suuid","This domain is associated with the company 6Sense Insights, Inc., which provides predictive analytics and account engagement services. It is primarily used for tracking and targeting in marketing automation and advertising.","hushly.com",[474],{"_77":475,"_389":472,"_390":34,"_176":426},"_hly_gvid","t.contentsquare.net",[478],{"_77":479,"_389":476,"_390":94,"_176":480},"_cs_*","This is a session cookie. This is a pattern type cookie where a random 13-digit number is appended to the prefix _cs_.",{"_77":537,"_389":504,"_390":34,"_176":538},{"_77":535,"_389":504,"_390":34,"_176":536},{"_77":533,"_389":504,"_390":34,"_176":534},{"_77":415,"_389":504,"_390":34,"_176":532},{"_77":509,"_389":504,"_390":94,"_176":511},{"_77":531,"_389":504,"_390":34,"_176":384},{"_77":530,"_389":507,"_390":34,"_176":384},{"_77":528,"_389":504,"_390":34,"_176":529},{"_77":526,"_389":504,"_390":34,"_176":527},{"_77":525,"_389":504,"_390":34,"_176":384},{"_77":523,"_389":504,"_390":34,"_176":524},{"_77":509,"_389":522,"_390":94,"_176":511},{"_77":520,"_389":507,"_390":34,"_176":521},{"_77":520,"_389":510,"_390":34,"_176":521},{"_77":479,"_389":504,"_390":34,"_176":480},{"_77":518,"_389":504,"_390":34,"_176":519},{"_77":425,"_389":516,"_390":34,"_176":517},{"_77":514,"_389":504,"_390":34,"_176":515},{"_77":512,"_389":504,"_390":34,"_176":513},{"_77":509,"_389":510,"_390":94,"_176":511},{"_77":506,"_389":507,"_390":34,"_176":508},{"_77":503,"_389":504,"_390":94,"_176":505},"AMCVS_xxxxxAdobeOrg","nvidia.com","This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier.","_rdt_pn","www.nvidia.com","This cookie name is associated with www.mind.org.uk which is used for marketing purposes.","AMP_*","build.nvidia.com","Supports Amplitude product analytics.","_gcl_au","Used by Google AdSense for experimenting with advertisement efficiency across websites using their services","_mkto_trk","This cookie is associated with an email marketing service provided by Marketo. This tracking cookie allows a website to link visitor behaviour to the recipient of an email marketing campaign, to measure campaign effectiveness.","investor.nvidia.com","This cookie is associated with Eventbrite and is used to deliver content tailored to the end user's interests and improve content creation. This cookie is also used for event-booking purposes.","_gat_gtag_UA_140825383_2","Google Analytics","_rdt_uuid","This cookie is set by Reddit and is used for tracking the views of embedded videos and performance of the advertisements.","catalog.ngc.nvidia.com","_uetsid","This cookie is used by Bing to determine what ads should be shown that may be relevant to the end user perusing the site. ","kndctr_F207D74D549850760A4C98C6_AdobeOrg_bc_session_id","ttcsid_XXXXXXXXXXXXXXXXXXXXCategory","This cookie name is associated with TikTok which is used to track your activity on the platform, including how you interact with their embedded services on other websites.This cookie is associated with TikTok. It helps track your activity on the platform, including how you interact with their embedded services on other websites.","_fbp","Used by Facebook to deliver a series of advertisement products such as real time bidding from third party advertisers","_zitok","_twpid","This cookie is typically associated with the use of Taptap Digital, a company specializing in digital advertising. It is used for tracking and ad personalization purposes.","_tt_enable_cookie","This cookie name is associated with TikTok which is used to collect data about behavior and purchases on the website and to measure the effect of advertising. It is also used to track website activity to help optimize advertising efforts.","AMCV_xxxxxAdobeOrg","This cookie is used to identify a unique visitor for tracking purposes by Adobe Experience Cloud.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.","ttcsid","This cookie name is associated with TikTok which is used to enable TikTok Ads session tracking by assigning a unique session ID to users who click on TikTok ads, allowing for the attribution of user behavior and conversions within the same session.This cookie is associated with TikTok. It helps track your activity on the platform, including how you interact with their embedded services on other websites.","C0003","Personalization Cookies","These cookies collect data about how you have interacted with our website to help us improve your web experience, such as which pages you have visited. These cookies may store a unique ID so that our system will remember you when you return. They may be set by us or by third party providers whose services we have added to our pages. These cookies enable us to provide enhanced website functionality and personalization as well as make the marketing messages we send to you more relevant to your interests. If you do not allow these cookies, then some or all of these services may not function properly.",[573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597],[544,545,546,547,548],{"_382":458,"_204":458,"_176":384,"_355":568},{"_382":432,"_204":432,"_176":384,"_355":563},{"_382":558,"_204":558,"_176":384,"_355":559},{"_382":553,"_204":553,"_176":384,"_355":554},{"_382":549,"_204":549,"_176":384,"_355":550},"nvidia.partners",[551],{"_77":552,"_389":549,"_390":34,"_176":426},"edge","app.hushly.com",[555],{"_77":556,"_389":553,"_390":34,"_176":557},"*CORS","This domain is associated with Hushly, a platform that provides lead conversion solutions for content marketing by using personalization and content engagement strategies.","github.com",[560],{"_77":561,"_389":558,"_390":34,"_176":562},"_octo","This domain is owned by Github. The main business activity is: Source code repository and collaboration platform",[564,565],{"_77":567,"_389":432,"_390":34,"_176":436},{"_77":566,"_389":432,"_390":34,"_176":436},"lidc","li_gc",[569,570],{"_77":572,"_389":458,"_390":34,"_176":462},{"_77":571,"_389":458,"_390":34,"_176":462},"imid_*","imid",{"_77":598,"_389":507,"_390":34,"_176":600},{"_77":629,"_389":504,"_390":34,"_176":630},{"_77":598,"_389":628,"_390":34,"_176":600},{"_77":626,"_389":504,"_390":94,"_176":627},{"_77":624,"_389":504,"_390":34,"_176":625},{"_77":623,"_389":606,"_390":94,"_176":384},{"_77":598,"_389":602,"_390":34,"_176":600},{"_77":621,"_389":504,"_390":34,"_176":622},{"_77":598,"_389":510,"_390":34,"_176":600},{"_77":609,"_389":507,"_390":34,"_176":384},{"_77":598,"_389":620,"_390":34,"_176":600},{"_77":618,"_389":504,"_390":34,"_176":619},{"_77":615,"_389":616,"_390":34,"_176":617},{"_77":613,"_389":614,"_390":34,"_176":384},{"_77":598,"_389":610,"_390":34,"_176":600},{"_77":612,"_389":504,"_390":34,"_176":384},{"_77":598,"_389":611,"_390":34,"_176":600},{"_77":609,"_389":610,"_390":34,"_176":384},{"_77":608,"_389":606,"_390":94,"_176":384},{"_77":598,"_389":607,"_390":34,"_176":600},{"_77":598,"_389":606,"_390":34,"_176":600},{"_77":598,"_389":605,"_390":34,"_176":600},{"_77":604,"_389":504,"_390":94,"_176":600},{"_77":601,"_389":602,"_390":94,"_176":603},{"_77":598,"_389":599,"_390":34,"_176":600},"_gd_*","info.nvidia.com","This cookie contains no identifying information and is used for diagnostic purposes by Impact Radius, a service we use to track signup commissions for our affiliate program. We have categorized it under Functionality because it is necessary for the operation of our affiliate program.","nv_country_code","developer.nvidia.com","This cookie is likely used to store the country code of the visitor to provide localized content and possibly for legal compliance with regional data privacy laws.","_gdxxxxxxxxxxxxx","nvidianews.nvidia.com","docs.api.nvidia.com","research.nvidia.com","readme_library","wcmmode","ai-podcast.nvidia.com","resources.nvidia.com","geo_locator","openedx-language-preference","learn.nvidia.com","doxygen_width","raytracing-docs.nvidia.com","This cookie is likely used to remember the width preferences of a sidebar or interface element within a documentation platform like Doxygen.","_sfid_eb78","This cookie is categorized as Functionality Cookie.","crowdsource.nvidia.com","mbox","Cookie set by Adobe SiteCatalyst analytics software - used for measuring the performance of page content using A/B split testing","readme_language","vid","This cookie name 'vid' is used for tracking the search request made by the user on the 'Find a practitioner' page.","at_check","Used by Adobe Target to check if cookies are enabled/supported on the browser","blogs.nvidia.com","nvHeadless","This cookie is likely used to track if a user is using the site in a 'headless' non-GUI mode, which could be for accessibility reasons or for automated processes.","C0002","Performance Cookies","These cookies are used to provide quantitative measures of our website visitors, such as the number of times you visit, time on page, your mouse movements, scrolling, clicks and keystroke activity on the websites; other browsing, search, or product research behavior; and what brought you to our site. These cookies may store a unique ID so that our system will remember you when you return. Information collected with these cookies is used to measure and find ways to improve website performance.",[656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684],[636,637,638,639],{"_382":651,"_204":651,"_176":384,"_355":652},{"_382":646,"_204":646,"_176":384,"_355":647},{"_382":445,"_204":445,"_176":384,"_355":643},{"_382":558,"_204":558,"_176":384,"_355":640},[641],{"_77":642,"_389":558,"_390":94,"_176":562},"_gh_sess",[644],{"_77":645,"_389":445,"_390":94,"_176":452},"YSC","bizible.com",[648],{"_77":649,"_389":646,"_390":34,"_176":650},"_BUID","Bizible is a marketing attribution software that tracks the performance of marketing efforts and connects them to revenue, primarily used for B2B environments.","a.usbrowserspeed.com",[653],{"_77":654,"_389":651,"_390":34,"_176":655},"tuid","This domain is owned by Ookla which provides internet speed testing services through its Speedtest application.",{"_77":726,"_389":504,"_390":34,"_176":727},{"_77":711,"_389":725,"_390":94,"_176":712},{"_77":694,"_389":507,"_390":34,"_176":619},{"_77":694,"_389":607,"_390":34,"_176":619},{"_77":723,"_389":504,"_390":34,"_176":724},{"_77":711,"_389":510,"_390":94,"_176":712},{"_77":721,"_389":504,"_390":34,"_176":722},{"_77":711,"_389":507,"_390":94,"_176":712},{"_77":719,"_389":606,"_390":34,"_176":720},{"_77":711,"_389":628,"_390":94,"_176":712},{"_77":691,"_389":507,"_390":34,"_176":693},{"_77":717,"_389":504,"_390":94,"_176":718},{"_77":715,"_389":504,"_390":34,"_176":716},{"_77":713,"_389":504,"_390":94,"_176":714},{"_77":711,"_389":602,"_390":94,"_176":712},{"_77":709,"_389":504,"_390":34,"_176":710},{"_77":707,"_389":504,"_390":34,"_176":708},{"_77":705,"_389":504,"_390":94,"_176":706},{"_77":703,"_389":611,"_390":34,"_176":704},{"_77":691,"_389":602,"_390":34,"_176":693},{"_77":701,"_389":504,"_390":34,"_176":702},{"_77":699,"_389":504,"_390":94,"_176":700},{"_77":697,"_389":504,"_390":34,"_176":698},{"_77":695,"_389":504,"_390":34,"_176":696},{"_77":694,"_389":504,"_390":34,"_176":619},{"_77":691,"_389":692,"_390":34,"_176":693},{"_77":689,"_389":504,"_390":34,"_176":690},{"_77":687,"_389":504,"_390":94,"_176":688},{"_77":685,"_389":504,"_390":34,"_176":686},"_ga_xxxxxxxxxx","Used by Google Analytics to identify and track an individual session with your device.","s_ppvl","This cookie is set by Adobe Analytics to store information on the percentage of the page displayed to the end user.","coveo_visitorId","This cookie name is associated with Coveo which is used to store a unique user ID for marketing purposes and to track the number of distinct users who submitted a query or clicked an item, counting them only once even if they did the same query or clicked the same item over the course of many visits.","_dd_s","marketplace.nvidia.com","Datadog Cookie used to group all events generated from a unique user session across multiple pages. It contains the current session ID, whether the session is excluded due to sampling, and the expiration date of the session. The cookie is extended for an extra 15 minutes every time the user interacts with the website, up to the maximum user session duration (4 hours).","nvweb_A","_ga","This cookie name is associated with Google Universal Analytics - which is a significant update to Google's more commonly used analytics service. This cookie is used to distinguish unique users by assigning a randomly generated number as a client identifier. It is included in each page request in a site and used to calculate visitor, session and campaign data for the sites analytics reports. By default it is set to expire after 2 years, although this is customisable by website owners.","_uetvid","This is a cookie utilised by Microsoft Bing Ads and is a tracking cookie. It allows us to engage with a user that has previously visited our website.","tp","This cookie is associated with Adobe Analytics site tracking. It registers if the website's scroll-depth detection is active. This function remembers how far the user has scrolled on the current session across the website's sub-pages.","_hly_vid","This cookie _hly_vid is used to record website and server performance with each visit to the site. The data is aggregated and analyzed; therefore, it remains anonymous upon use.","_session_id","This cookie creates an interim session ID used as an in-session user ID.\n","s_cc","This cookie is associated with the Adobe Site Catalyst. It determines whether cookies are enabled in the web browser.","s_ecid","Adobe Analytics cookie containing the the Adobe Experience Cloud 1st party visitor id if the Analytics AMCV visitor id is not found.","_hjSessionUser_xxxxxx","Hotjar cookie that is set when a user first lands on a page with the Hotjar script. It is used to persist the Hotjar User ID, unique to that site on the browser. This ensures that behavior in subsequent visits to the same site will be attributed to the same user ID.","_hjHasCachedUserAttributes","This cookie name is associated with Hotjar which is used to know whether the data set in _hjUserAttributes Local Storage item is up to date or not.","s_ppv","This cookie is associated with Adobe Analytics site tracking and is used to measure a user's scroll activity to see how much of a page they view before moving to another page.","_gid","This cookie name is associated with Google Universal Analytics. This appears to be a new cookie and as of Spring 2017 no information is available from Google. It appears to store and update a unique value for each page visited.","_hjTLDTest","When the Hotjar script executes we try to determine the most generic cookie path we should use, instead of the page hostname. This is done so that cookies can be shared across subdomains (where applicable). To determine this, we try to store the _hjTLDTest cookie for different URL substring alternatives until it fails. After this check, the cookie is removed.","ekfls-2025-03-27","This cookie name is associated with readme.io which is used to help maintain data for the API reference support page.","s_getNewRepeat","This cookie is used to determine whether a visitor is a new visitor or a repeat visitor to the site, and is used for analytical purposes.","_hly_sid","This cookie is likely associated with website analytics, as the prefix '_hly_' suggests a connection to Holistics, a business intelligence and analytics platform.","docs.nvidia.com","_hjSession_xxxxxx","A cookie that holds the current session data. This ensues that subsequent requests within the session window will be attributed to the same Hotjar session.","C0001","Required Cookies","These cookies enable core functionality such as security, network management, and accessibility. These cookies are required for the site to function and cannot be turned off.",[873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945],[733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757],{"_382":870,"_204":870,"_176":384,"_355":871},{"_382":864,"_204":864,"_176":384,"_355":865},{"_382":861,"_204":861,"_176":384,"_355":862},{"_382":849,"_204":849,"_176":384,"_355":850},{"_382":846,"_204":846,"_176":384,"_355":847},{"_382":843,"_204":843,"_176":384,"_355":844},{"_382":838,"_204":838,"_176":384,"_355":839},{"_382":445,"_204":445,"_176":384,"_355":835},{"_382":832,"_204":832,"_176":384,"_355":833},{"_382":437,"_204":437,"_176":384,"_355":830},{"_382":432,"_204":432,"_176":384,"_355":828},{"_382":823,"_204":823,"_176":384,"_355":824},{"_382":818,"_204":818,"_176":384,"_355":819},{"_382":813,"_204":813,"_176":384,"_355":814},{"_382":810,"_204":810,"_176":384,"_355":811},{"_382":558,"_204":558,"_176":384,"_355":807},{"_382":417,"_204":417,"_176":384,"_355":804},{"_382":553,"_204":553,"_176":384,"_355":797},{"_382":549,"_204":549,"_176":384,"_355":791},{"_382":785,"_204":785,"_176":384,"_355":786},{"_382":780,"_204":780,"_176":384,"_355":781},{"_382":775,"_204":775,"_176":384,"_355":776},{"_382":771,"_204":771,"_176":384,"_355":772},{"_382":766,"_204":766,"_176":384,"_355":767},{"_382":758,"_204":758,"_176":384,"_355":759},"polyfill.io",[760,761],{"_77":764,"_389":758,"_390":34,"_176":765},{"_77":762,"_389":758,"_390":34,"_176":763},"cf_ob_info","This cookie is associated with sites using CloudFlare. It is used to improve page load times and to override any security restrictions based on the visitors IP address. It does not contain any user identification information.","cf_use_ob","This cookie is associated with sites using CloudFlare. It is used to improve page load times and to override any security restrictions based on the visitors IP address. It does not contain any user identification information. ","www.recaptcha.net",[768],{"_77":769,"_389":766,"_390":34,"_176":770},"_GRECAPTCHA","This domain is used by Google reCAPTCHA, which provides spam protection services to websites by detecting if a user is a human or a bot.","api2.hcaptcha.com",[773],{"_77":774,"_389":771,"_390":34,"_176":426},"__cflb","instagram.com",[777],{"_77":778,"_389":775,"_390":34,"_176":779},"csrftoken","Instagram is a social networking service owned by Facebook, Inc. It's designed for sharing photos and videos from a smartphone. The service also uses cookies for various purposes, including analytics, personalization, and advertising.","readme.io",[782],{"_77":783,"_389":780,"_390":34,"_176":784},"__cf_bm","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. As part of our bot management service, this cookie helps manage incoming traffic that matches criteria associated with bots.","nvidiacorp.us-5.evergage.com",[787,788],{"_77":790,"_389":785,"_390":34,"_176":426},{"_77":789,"_389":785,"_390":34,"_176":426},"AWSALBTG","AWSALBTGCORS",[792,793],{"_77":795,"_389":549,"_390":34,"_176":796},{"_77":794,"_389":549,"_390":34,"_176":426},"ak_bmsc","bm_mi","This domain is likely associated with NVIDIA's partner program, which could involve marketing, sales, and support services for partners.",[798,799,800],{"_77":803,"_389":553,"_390":34,"_176":426},{"_77":802,"_389":553,"_390":94,"_176":426},{"_77":801,"_389":553,"_390":34,"_176":426},"AWSALBCORS","JSESSIONID","AWSALB",[805],{"_77":783,"_389":417,"_390":34,"_176":806},"This is a CloudFoundry cookie",[808],{"_77":809,"_389":558,"_390":34,"_176":562},"logged_in","hcaptcha.com",[812],{"_77":783,"_389":810,"_390":34,"_176":806},"tracking.intentsify.io",[815],{"_77":816,"_389":813,"_390":34,"_176":817},"userId","Used to track usage of the embedded video player.","static.reo.dev",[820],{"_77":821,"_389":818,"_390":34,"_176":822},"cookietest","Common cookie name could have a number of different origins. Where this is first party and a session cookie, its most likely to do with checking to see if the browser is set to block or allow cookies.","www.datadoghq-browser-agent.com",[825],{"_77":826,"_389":823,"_390":34,"_176":827},"dd_cookie_test_","dd_cookie_test",[829],{"_77":783,"_389":432,"_390":34,"_176":806},[831],{"_77":783,"_389":437,"_390":34,"_176":806},"supabase.co",[834],{"_77":783,"_389":832,"_390":34,"_176":806},[836],{"_77":837,"_389":445,"_390":34,"_176":452},"VISITOR_PRIVACY_METADATA","dosa-prd.azurewebsites.net",[840],{"_77":841,"_389":838,"_390":34,"_176":842},"access_token","This cookie is used to obtain the permissions for users of the portal to allow for API access in order to retrieve information required to perform portal functions.","w.hcaptcha.com",[845],{"_77":783,"_389":843,"_390":34,"_176":806},"cdn.readme.io",[848],{"_77":783,"_389":846,"_390":34,"_176":806},"queue-it.net",[851,852,853,854,855],{"_77":860,"_389":849,"_390":34,"_176":384},{"_77":859,"_389":849,"_390":34,"_176":384},{"_77":858,"_389":849,"_390":34,"_176":384},{"_77":857,"_389":849,"_390":34,"_176":384},{"_77":856,"_389":849,"_390":34,"_176":384},"Queue-it-{queueId}","Queue-it-{dmonvidia }________{eventId}","Queue-it-token","queueitsoftblock_{queueId}","Queue-it-{nvidia}________{eventId}","x.com",[863],{"_77":783,"_389":861,"_390":34,"_176":784},"api.hcaptcha.com",[866,867],{"_77":869,"_389":864,"_390":34,"_176":426},{"_77":774,"_389":864,"_390":34,"_176":868},"This domain is associated with hCaptcha, a service that provides CAPTCHA and reCAPTCHA alternatives for user verification and bot protection.","hmt_id","vimeo.com",[872],{"_77":783,"_389":870,"_390":34,"_176":806},{"_77":1006,"_389":504,"_390":34,"_176":1037},{"_77":1035,"_389":599,"_390":94,"_176":1036},{"_77":1028,"_389":997,"_390":94,"_176":1029},{"_77":1034,"_389":692,"_390":94,"_176":384},{"_77":1032,"_389":504,"_390":34,"_176":1033},{"_77":790,"_389":1018,"_390":34,"_176":957},{"_77":965,"_389":1027,"_390":94,"_176":967},{"_77":789,"_389":956,"_390":34,"_176":957},{"_77":968,"_389":1027,"_390":34,"_176":969},{"_77":1030,"_389":504,"_390":94,"_176":1031},{"_77":1028,"_389":1004,"_390":94,"_176":1029},{"_77":962,"_389":1027,"_390":34,"_176":964},{"_77":1025,"_389":504,"_390":34,"_176":1026},{"_77":789,"_389":948,"_390":34,"_176":957},{"_77":953,"_389":1024,"_390":34,"_176":955},{"_77":801,"_389":954,"_390":34,"_176":970},{"_77":803,"_389":954,"_390":34,"_176":1021},{"_77":968,"_389":963,"_390":34,"_176":969},{"_77":1022,"_389":602,"_390":34,"_176":1023},{"_77":803,"_389":628,"_390":34,"_176":1021},{"_77":1019,"_389":504,"_390":34,"_176":1020},{"_77":795,"_389":628,"_390":34,"_176":1014},{"_77":991,"_389":607,"_390":94,"_176":384},{"_77":789,"_389":1018,"_390":34,"_176":957},{"_77":1016,"_389":956,"_390":94,"_176":1017},{"_77":980,"_389":504,"_390":34,"_176":971},{"_77":953,"_389":504,"_390":34,"_176":955},{"_77":1015,"_389":516,"_390":34,"_176":384},{"_77":795,"_389":504,"_390":34,"_176":1014},{"_77":803,"_389":948,"_390":34,"_176":1013},{"_77":1011,"_389":611,"_390":94,"_176":1012},{"_77":1009,"_389":504,"_390":94,"_176":1010},{"_77":1008,"_389":504,"_390":34,"_176":384},{"_77":1006,"_389":954,"_390":34,"_176":1007},{"_77":1005,"_389":516,"_390":34,"_176":384},{"_77":996,"_389":1004,"_390":94,"_176":998},{"_77":1002,"_389":607,"_390":34,"_176":1003},{"_77":1000,"_389":692,"_390":34,"_176":1001},{"_77":999,"_389":510,"_390":34,"_176":384},{"_77":996,"_389":997,"_390":94,"_176":998},{"_77":994,"_389":963,"_390":94,"_176":995},{"_77":992,"_389":504,"_390":34,"_176":993},{"_77":991,"_389":507,"_390":94,"_176":384},{"_77":962,"_389":966,"_390":34,"_176":964},{"_77":794,"_389":981,"_390":34,"_176":971},{"_77":989,"_389":507,"_390":34,"_176":990},{"_77":987,"_389":504,"_390":34,"_176":988},{"_77":985,"_389":504,"_390":34,"_176":986},{"_77":984,"_389":504,"_390":34,"_176":384},{"_77":826,"_389":507,"_390":34,"_176":983},{"_77":980,"_389":628,"_390":34,"_176":971},{"_77":783,"_389":599,"_390":34,"_176":982},{"_77":980,"_389":981,"_390":34,"_176":971},{"_77":979,"_389":516,"_390":34,"_176":384},{"_77":978,"_389":504,"_390":34,"_176":951},{"_77":976,"_389":963,"_390":34,"_176":977},{"_77":789,"_389":974,"_390":34,"_176":975},{"_77":973,"_389":516,"_390":34,"_176":384},{"_77":972,"_389":504,"_390":34,"_176":384},{"_77":965,"_389":963,"_390":94,"_176":967},{"_77":794,"_389":628,"_390":34,"_176":971},{"_77":801,"_389":628,"_390":34,"_176":970},{"_77":968,"_389":966,"_390":34,"_176":969},{"_77":965,"_389":966,"_390":94,"_176":967},{"_77":962,"_389":963,"_390":34,"_176":964},{"_77":960,"_389":956,"_390":94,"_176":961},{"_77":958,"_389":614,"_390":34,"_176":959},{"_77":790,"_389":956,"_390":34,"_176":957},{"_77":953,"_389":954,"_390":34,"_176":955},{"_77":783,"_389":606,"_390":34,"_176":952},{"_77":950,"_389":504,"_390":34,"_176":951},{"_77":801,"_389":948,"_390":34,"_176":949},{"_77":946,"_389":504,"_390":34,"_176":947},"LoginHints","Keeps users logged in across NVIDIA domains.","api.ngc.nvidia.com","This cookie is managed by AWS and is used for load balancing.","bm_so","This cookie name is used to load the site as quickly as possible and to recognize bots using Akamai.","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. As part of our bot management service, this cookie helps manage incoming traffic that matches criteria associated with bots.\nThis is a CloudFoundry cookie","OptanonConsent","nvid.nvidia.com","This cookie is set by the cookie compliance solution from OneTrust. It stores information about the categories of cookies the site uses and whether visitors have given or withdrawn consent for the use of each category. This enables site owners to prevent cookies in each category from being set in the users browser, when consent is not given. The cookie has a normal lifespan of one year, so that returning visitors to the site will have their preferences remembered. It contains no information that can identify the site visitor.","events.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","sessionid","This is a very generic cookie name that may have different purposes on different sites, but generally it will be some kind of anonymous session identifier.","_csrf","This cookie is used to prevent Cross-Site Request Forgery (CSRF) attacks, ensuring that each request made to the server is from the user's browser and is intentional.","LSKey-c$CookieConsentPolicy","enterprise-support.nvidia.com","Used to apply end-user cookie consent preferences set by our client-side utility.Custom- Short Duration. Unique ID of an Enquiry- used to validate access to case, and load exisiting data.\n","renderCtx","academicgrants.nvidia.com","Used to store site parameters in the session for reuse across requests by a single client for functionality and performance reasons.","CookieConsentPolicy","Used to apply end-user cookie consent preferences set by our client-side utility.","This cookie is managed by AWS and is used for load balancing.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","This cookie is associated with Akamai and is used to differentiate between traffic from humans and bots.","nv_co","__uxq412__ses.88c1","learn.learn.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.","pctrk","Used to count page views by unauthenticated users against license usage.","bm_s","bpazaws52gukakzc__ctrl0_ctl36_uccaptcha","bm_sv","store.nvidia.com","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. As part of our bot management service, this cookie helps manage incoming traffic that matches criteria associated with bots.\n","This cookie name is used by DataDog to determine if cookies are supported on the website.dd_cookie_test","AMP_TLDTEST_xxxxxxxx","SESSlsd","This cookie is likely to be a session identifier used to maintain user session state across page requests.","mboxEdgeCluster","This cookie name is associated with Adobe Target which is used to communicate the correct edge cluster to at.js so that Target profiles can stay in sync as users navigate across a site.","_rdt_em","This cookie name is associated with Reddit which is used to manage session state and user interactions.","megaNavCollapsed","_abck","The _abck cookie is associated with Akamai's Bot Manager, which is used to prevent fraud and abuse by safeguarding online interactions and detecting irregularities that could suggest malicious activity, such as bot-driven attacks or hacking attempts.","idccsrf","This cookie name is associated with Salesforce which is used to track CrossSiteRequestForgery validation for certain single sign-on (SSO) flows.","ApplicationGatewayAffinity","partners.nvidia.com","This cookie is used to maintain a user session by the server in a load balanced environment, to ensure the user has a consistent experience.","AMP_TEST_xxxxxxxx","bm_lso","This cookie name is associated with Akamai which is used to load the site as quickly as possible and to recognize bots.","SSESS###########","This cookie is likely to be a session cookie used to maintain an anonymized user session by the server in a secure environment, often seen in sites built with the Drupal content management system.","nvdeveloper.nvidia.com","__uxq412__id.88c1","OptanonAlertBoxClosed","This cookie is set by websites using certain versions of the cookie law compliance solution from OneTrust. It is set after visitors have seen a cookie information notice and in some cases only when they actively close the notice down. It enables the website not to show the message more than once to a user. The cookie has a normal lifespan of one year and contains no personal information.","QueueITAccepted-SDFrts345E-V3_{eventId}","TEST_AMCV_COOKIE_WRITE","This cookie is used to test whether cookies are enabled in the browser. It is a temporary cookie used to determine if the browser accepts cookies.","XSRF-TOKEN","This cookie is written to help with site security in preventing Cross-Site Request Forgery attacks.This cookie helps with site security in preventing Cross-Site Request Forgery attacks.","AWS ELB application load balancer","This cookie is associated with Akamai. It is used to analyse traffic to determine if it is automated traffic generated by bots or a human user.","bpazaws52gukakzc__ctrl0_ctl78_list_ctl09_systemcaptcha","PHPSESSID","PHP session cookie associated with embedded content from this domain.\n","base.manager.learn.nvidia.com","bm_ss","This cookie is used to help protect websites from automated bot traffic.","AWS ELB application load balancerUsed to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","_devzone_session","This cookie is likely used to maintain a user session on the website by the server. It is common for session identifiers to be used to keep users logged in and track their interaction with the site during a session.","docs.ngc.nvidia.com","bm_sz","This cookie is used by Akamai to optimize site performance and security. It is typically associated with the delivery of web content and services.","vcalliance.nvidia.com","ASP.NET_SessionId","General purpose platform session cookie, used by sites written with Microsoft .NET based technologies. Usually used to maintain an anonymised user session by the server.","com.adobe.alloy.getTld","This cookie name is associated with the Adobe WebSDK which is used to determine the top-most domain that can accept cookies.","SESSls","This cookie is likely to be a session identifier, used to maintain a user's session state across page requests.","c_code","BIGipServerx","This cookie name is associated with the BIG-IP product suite from company F5. Usually associated with managing sessions on load balanced servers, to ensure user requests are routed consistently to the correct server. The common root is BIGipServer most commonly followed by a domain name, usually the one that it is hosted on, but not always.","This cookie is set by websites using certain versions of the cookie law compliance solution from OneTrust. It is set after visitors have seen a cookie information notice and in some cases only when they actively close the notice down. It enables the website not to show the message more than once to a user. The cookie has a one year lifespan and contains no personal information.","default","

NVIDIA uses cookies to improve your experience on our web site. We and our third-party partners also use cookies and other tools to collect and record information you provide as well as information about your interactions with our websites for performance improvement, analytics, and to assist in marketing efforts. By clicking \"Accept All\", you consent to our use of cookies and other tools as described in our Cookie Policy. You can manage your cookie settings by clicking on \"Manage Settings.\" By continuing to use this site or by clicking one of the buttons below, you agree to our Terms of Service (which contains important waivers). Please see our Privacy Policy for more information on our privacy practices.

","gpc","

We have detected the Global Privacy Control (GPC) signal and recorded your rejection of all optional cookies on this site for this browser. You can manage your cookie settings by clicking on \"Manage Settings\". Please see our Cookie Policy for more information. To opt out of non-cookie personal information \"sales\" / \"sharing\" for targeted advertising purposes, please visit the NVIDIA Preference Center. Please see our Privacy Policy for more information on our privacy practices.

","gpcLoggedIn","

We have detected the Global Privacy Control Signal (GPC) and have opted you out of all optional cookies on this browser. You can manage your cookie settings by clicking on \"Manage Settings\". Please see our Cookie Policy for more information. We have also opted you out of \"sharing\"/\"sales\" of personal information outside of cookies. You can manage these settings in the NVIDIA NVIDIA Preference Center. Please see our Privacy Policy for more information.

","gpcLoggedInOverridden","

We have detected the Global Privacy Control Signal (GPC) and have opted you out of all optional cookies on this browser. You can manage your cookie settings by clicking on \"Manage Settings\". Please see our Cookie Policy for more information. We have also opted you out of \"sharing\"/\"sales\" of personal information outside of cookies which overrides at least one of your previous settings. You can manage them in the NVIDIA Preference Center. Please see our Privacy Policy for more information.

",{"_728":16,"_631":59,"_539":59,"_359":59,"_349":59},"hasConsented","gpcApplied","showBanner","geolocation",{"_1052":1053,"_1054":1055},"country","US","state","OR","query","categories",[1075,1076,1077,1078,1079],"optionUrls",[1063,1064,1065,1066,1067,1068,1069,1070,1071,1072,1073,1074],"total",12,"/orgs/nim/deepseek-ai/containers/deepseek-r1/-","/orgs/nim/nvidia/containers/llama-3.1-nemotron-70b-instruct/-","/orgs/nvidia/-/containers/pytorch/-","/orgs/nvidia/omniverse/collections/kit/-","/orgs/nvidia/-/collections/deepstream_sdk/-","/orgs/nvidia/omniverse/collections/kit-appstreaming-collection/-","/orgs/nvidia/research/models/stylegan3/-","/orgs/nvidia/tao/models/peoplenet/-","/orgs/nvidia/tao/models/trafficcamnet/-","/orgs/nvidia/riva/resources/riva_quickstart/-","/orgs/nvidia/-/helm-charts/gpu-operator/-","/orgs/nvidia/-/helm-charts/k8s-nim-operator/-",{"_20":1154,"_1080":1155,"_1082":59},{"_20":1119,"_1080":1120,"_1082":57},{"_20":1102,"_1080":1103,"_1082":1104},{"_20":1094,"_1080":1095,"_1082":1096},{"_20":21,"_1080":1081,"_1082":19},"items",[1083,1084],"startIndex",{"_20":21,"_204":1091,"_170":1086,"_172":-7,"_199":1092,"_207":1088,"_232":1093,"_1090":1073},{"_20":21,"_204":1085,"_170":1086,"_172":-7,"_199":1087,"_207":1088,"_232":1089,"_1090":1074},"NVIDIA NIM Operator","nvidia","k8s-nim-operator","NVIDIA",[],"url","GPU Operator","gpu-operator",[],"resources",[1097],9,{"_20":1094,"_204":1098,"_170":1086,"_172":1099,"_199":1100,"_207":1088,"_232":1101,"_1090":1072},"Riva Skills Quick Start","riva","riva_quickstart",[],"models",[1105,1106,1107],6,{"_20":1102,"_204":1115,"_170":1086,"_172":1116,"_199":1117,"_207":1088,"_232":1118,"_1090":1069},{"_20":1102,"_204":1112,"_170":1086,"_172":1109,"_199":1113,"_207":1088,"_232":1114,"_1090":1070},{"_20":1102,"_204":1108,"_170":1086,"_172":1109,"_199":1110,"_207":1088,"_232":1111,"_1090":1071},"TrafficCamNet","tao","trafficcamnet",[],"PeopleNet","peoplenet",[],"StyleGAN3 pretrained models","research","stylegan3",[],"collections",[1121,1122,1123],{"_20":1119,"_204":1151,"_170":1086,"_172":1125,"_199":1152,"_207":1088,"_232":1153,"_1090":1066},{"_20":1119,"_204":1148,"_170":1086,"_172":-7,"_199":1149,"_207":1088,"_232":1150,"_1090":1067},{"_20":1119,"_204":1124,"_170":1086,"_172":1125,"_199":1126,"_207":1088,"_232":1127,"_1090":1068},"Omniverse Kit App Streaming","omniverse","kit-appstreaming-collection",[1128,1129,1130],{"_77":1142,"_204":1143,"_201":1144,"_211":1145,"_1135":1146},{"_77":1125,"_204":1138,"_201":1139,"_211":1134,"_1135":1140},{"_77":1131,"_204":1132,"_201":1133,"_211":1134,"_1135":1136},"omniverse-dev","NVIDIA Developer Program","Join the Developer Program for access to free tools, support, and tech resources.","https://store-images.s-microsoft.com/image/apps.33936.6f1bcf42-55d0-45d1-b4b6-f08c68a50bbe.e91ca707-db64-49d6-9761-4781590a9685.7ba64fc5-7c44-4864-a5e6-7bde05126935","supportedFeatures",[1137],"UNIFIED_CATALOG","NVIDIA Omniverse","NVIDIA Omniverse is a platform of APIs, services, and software development kits (SDKs) that enable developers to build generative AI-enabled tools and applications.",[1137,1141],"SHAREABLE_TO_USER_GROUPS","nv-ai-enterprise","NVIDIA AI Enterprise","Accelerate your AI agent development","https://assets.ngc.nvidia.com/products/catalog/images/product-NVAIE.jpg",[1137,1141,1147],"NGC_CONSOLE","DeepStream SDK","deepstream_sdk",[],"Omniverse Kit (FB)","kit",[1128,1129,1130],"containers",[1156,1157,1158],{"_20":1154,"_204":1170,"_170":1163,"_172":1171,"_199":1172,"_207":1088,"_232":1173,"_1090":1063},{"_20":1154,"_204":1162,"_170":1163,"_172":1086,"_199":1164,"_207":1088,"_232":1165,"_1090":1064},{"_20":1154,"_204":1159,"_170":1086,"_172":-7,"_199":1160,"_207":1088,"_232":1161,"_1090":1065},"PyTorch","pytorch",[],"Llama-3.1-Nemotron-70B-Instruct","nim","llama-3.1-nemotron-70b-instruct",[1128,1166],{"_77":1167,"_204":1132,"_201":1133,"_211":1168,"_1135":1169},"nim-dev","https://assets.ngc.nvidia.com/products/catalog/images/product-nim-dev.jpg",[1137],"DeepSeek-R1","deepseek-ai","deepseek-r1",[1128,1166],"ownerOrgs",[],"memberOrgs",[],"externalOrgs",[],"apiKey","2b44f86fea50e90ffd2db29ee2028419","consentGranted","applicationId","4c857e4f-5ffa-45fa-b75e-af773c22f0ad","clientToken","pubb6927db33dae60ba5031a186cde0242a","site","datadoghq.com","service","catalog-ui","env","sessionSampleRate",100,"sessionReplaySampleRate","compressIntakeRequests","storeContextsAcrossPages","defaultPrivacyLevel","mask-user-input","trackViewsManually","trackingConsent","not-granted",{"_1203":1204,"_1205":298,"_1206":34,"_1207":1208,"_1080":1209,"_1210":1211,"_1212":1204,"_1213":34,"_1214":34,"_1215":34,"_1216":1217},"appName","ngc-catalog","appOrigin","hideOnPrivateOrg","icon","ObjectsModules2",[1218,1219,1220,1221,1222,1223,1224],"menuIcon","editor-swatches","productName","requiresAllScopes","requiresLogin","requiresOrgLevelScopesOnly","title","Catalog",{"_1216":1246,"_50":1247,"_1210":1248},{"_1239":1240,"_1216":1241,"_50":1242,"_1212":1142},{"_1216":1237,"_50":1238,"_1210":1211},{"_1216":1234,"_50":1235,"_1210":1236},{"_1216":1231,"_50":1232,"_1210":1233},{"_1216":1228,"_50":1229,"_1210":1230},{"_1216":1225,"_50":1226,"_1210":1227},"Resources","/resources","misc-library","Models","/models","misc-neural-network","Helm Charts","/helm-charts","misc-ship-wheel","Containers","/containers","3d-cube","Collections","/collections","access",[1243],"Enterprise Catalog","/enterprise",[1244,1245],"NVAIE","READ","Explore Catalog","/","common-home",{"_120":121,"_122":123,"_124":125,"_126":127,"_128":129,"_130":131},{"_119":34}]